Prediction of promiscuous peptides that bind HLA class I molecules

Promiscuous T-cell epitopes make ideal targets for vaccine development. We report here a computational system, multipred, for the prediction of peptide binding to the HLA-A2 supertype. It combines a novel representation of peptide/MHC interactions with a hidden Markov model as the prediction algorithm. multipred is both sensitive and specific, and demonstrates high accuracy of peptide-binding predictions for HLA-A*0201, *0204, and *0205 alleles, good accuracy for *0206 allele, and marginal accuracy for *0203 allele. multipred replaces earlier requirements for individual prediction models for each HLA allelic variant and simplifies computational aspects of peptide-binding prediction. Preliminary testing indicates that multipred can predict peptide binding to HLA-A2 supertype molecules with high accuracy, including those allelic variants for which no experimental binding data are currently available.

Cost-Effectiveness of Palliation of Unresectable Esophageal Cancer

Introduction Different modalities of palliation for obstructive symptoms in patients with unresectable esophageal cancer (EC) exist. However, these therapeutic alternatives have significant differences in costs and effectiveness. Methods A Markov model was designed to compare the cost-effectiveness (CE) of self-expandable stent (SES), brachytherapy and laser in the palliation of unresectable EC. Patients were assigned to one of the strategies, and the improvement in swallowing function was compared given the treatment efficacy, probability of survival, and risks of complications associated to each strategy. Probabilities and parameters for distribution were based on a 9-month time frame. Results Under the base-case scenario, laser has the lowest CE ratio, followed by brachytherapy at an incremental cost-effectiveness ratio (ICER) of $4,400.00, and SES is a dominated strategy. In the probabilistic analysis, laser is the strategy with the highest probability of cost-effectiveness for willingness to pay (WTP) values lower than $3,201 and brachytherapy for all WTP yielding a positive net health benefit (NHB) (threshold $4,440). The highest probability of cost-effectiveness for brachytherapy is 96%, and consequently, selection of suboptimal strategies can lead to opportunity losses for the US health system, ranging from US$ 4.32 to US$ 38.09 million dollars over the next 5-20 years. Conclusion Conditional to the WTP and current US Medicare costs, palliation of unresectable esophageal cancers with brachytherapy provides the largest amount of NHB and is the strategy with the highest probability of CE. However, some level of uncertainly remains, and wrong decisions will be made until further knowledge is acquired.

The genome of the blood fluke Schistosoma mansoni

Schistosoma mansoni is responsible for the neglected tropical disease schistosomiasis that affects 210 million people in 76 countries. Here we present analysis of the 363 megabase nuclear genome of the blood fluke. It encodes at least 11,809 genes, with an unusual intron size distribution, and new families of micro-exon genes that undergo frequent alternative splicing. As the first sequenced flatworm, and a representative of the Lophotrochozoa, it offers insights into early events in the evolution of the animals, including the development of a body pattern with bilateral symmetry, and the development of tissues into organs. Our analysis has been informed by the need to find new drug targets. The deficits in lipid metabolism that make schistosomes dependent on the host are revealed, and the identification of membrane receptors, ion channels and more than 300 proteases provide new insights into the biology of the life cycle and new targets. Bioinformatics approaches have identified metabolic chokepoints, and a chemogenomic screen has pinpointed schistosome proteins for which existing drugs may be active. The information generated provides an invaluable resource for the research community to develop much needed new control tools for the treatment and eradication of this important and neglected disease.

A new method for analysing the equilibrium and time-dependent behaviour of Markovian models

Many large-scale stochastic systems, such as telecommunications networks, can be modelled using a continuous-time Markov chain. However, it is frequently the case that a satisfactory analysis of their time-dependent, or even equilibrium, behaviour is impossible. In this paper, we propose a new method of analyzing Markovian models, whereby the existing transition structure is replaced by a more amenable one. Using rates of transition given by the equilibrium expected rates of the corresponding transitions of the original chain, we are able to approximate its behaviour. We present two formulations of the idea of expected rates. The first provides a method for analysing time-dependent behaviour, while the second provides a highly accurate means of analysing equilibrium behaviour. We shall illustrate our approach with reference to a variety of models, giving particular attention to queueing and loss networks. (C) 2003 Elsevier Ltd. All rights reserved.

Short-term Feature Space and Music Genre Classification

In music genre classification, most approaches rely on statistical characteristics of low-level features computed on short audio frames. In these methods, it is implicitly considered that frames carry equally relevant information loads and that either individual frames, or distributions thereof, somehow capture the specificities of each genre. In this paper we study the representation space defined by short-term audio features with respect to class boundaries, and compare different processing techniques to partition this space. These partitions are evaluated in terms of accuracy on two genre classification tasks, with several types of classifiers. Experiments show that a randomized and unsupervised partition of the space, used in conjunction with a Markov Model classifier lead to accuracies comparable to the state of the art. We also show that unsupervised partitions of the space tend to create less hubs.

Categorical data clustering using a minimum message length criterion

Research on cluster analysis for categorical data continues to develop, new clustering algorithms being proposed. However, in this context, the determination of the number of clusters is rarely addressed. We propose a new approach in which clustering and the estimation of the number of clusters is done simultaneously for categorical data. We assume that the data originate from a finite mixture of multinomial distributions and use a minimum message length criterion (MML) to select the number of clusters (Wallace and Bolton, 1986). For this purpose, we implement an EM-type algorithm (Silvestre et al., 2008) based on the (Figueiredo and Jain, 2002) approach. The novelty of the approach rests on the integration of the model estimation and selection of the number of clusters in a single algorithm, rather than selecting this number based on a set of pre-estimated candidate models. The performance of our approach is compared with the use of Bayesian Information Criterion (BIC) (Schwarz, 1978) and Integrated Completed Likelihood (ICL) (Biernacki et al., 2000) using synthetic data. The obtained results illustrate the capacity of the proposed algorithm to attain the true number of cluster while outperforming BIC and ICL since it is faster, which is especially relevant when dealing with large data sets.

Determining the number of clusters in categorical data

Cluster analysis for categorical data has been an active area of research. A well-known problem in this area is the determination of the number of clusters, which is unknown and must be inferred from the data. In order to estimate the number of clusters, one often resorts to information criteria, such as BIC (Bayesian information criterion), MML (minimum message length, proposed by Wallace and Boulton, 1968), and ICL (integrated classification likelihood). In this work, we adopt the approach developed by Figueiredo and Jain (2002) for clustering continuous data. They use an MML criterion to select the number of clusters and a variant of the EM algorithm to estimate the model parameters. This EM variant seamlessly integrates model estimation and selection in a single algorithm. For clustering categorical data, we assume a finite mixture of multinomial distributions and implement a new EM algorithm, following a previous version (Silvestre et al., 2008). Results obtained with synthetic datasets are encouraging. The main advantage of the proposed approach, when compared to the above referred criteria, is the speed of execution, which is especially relevant when dealing with large data sets.

Algorithms and methodologies for decision support in energy efficiency on buildings

Dissertação apresentada na faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

Adaptive filtering for high quality HMM based speech synthesis

In this work an adaptive filtering scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for Hidden Markov Model (HMM) based speech synthesis quality enhancement. The objective is to improve signal smoothness across HMMs and their related states and to reduce artifacts due to acoustic model's limitations. Both speech and artifacts are modelled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. Themodel parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The quality enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. The system's performance has been evaluated using mean opinion score tests and the proposed technique has led to improved results.

Spatio-Temporal data modeling in response to deforestation monitoring (a case study of small region in Riau Province, Indonesia)

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Economic Evaluation of Ticagrelor for Secondary Prevention Following Acute Coronary Syndromes

INTRODUCTION AND OBJECTIVES: To estimate the cost-effectiveness and cost-utility of ticagrelor in the treatment of patients with acute coronary syndromes (unstable angina or myocardial infarction with or without ST-segment elevation), including patients treated medically and those undergoing percutaneous coronary intervention or coronary artery bypass grafting. METHODS: A short-term decision tree and a long-term Markov model were used to simulate the evolution of patients' life-cycles. Clinical effectiveness data were collected from the PLATO trial and resource use data were obtained from the Hospital de Santa Marta database, disease-related group legislation and the literature. RESULTS: Ticagrelor provides increases of 0.1276 life years and 0.1106 quality-adjusted life years (QALYs) per patient. From a societal perspective these clinical gains entail an increase in expenditure of €610. Thus the incremental cost per life year saved is €4780 and the incremental cost per QALY is €5517. CONCLUSIONS: The simulation results show that ticagrelor reduces events compared to clopidogrel. The costs of ticagrelor are partially offset by lower costs arising from events prevented. The use of ticagrelor in clinical practice is therefore cost-effective compared to generic clopidogrel.

A Pilot Cost-Effectiveness Analysis of Treatments in Newly Diagnosed High-Grade Gliomas: The Example of 5-Aminolevulinic Acid Compared With White-Light Surgery

BACKGROUND: High-grade gliomas are aggressive, incurable tumors characterized by extensive diffuse invasion of the normal brain parenchyma. Novel therapies at best prolong survival; their costs are formidable and benefit is marginal. Economic restrictions thus require knowledge of the cost-effectiveness of treatments. Here, we show the cost-effectiveness of enhanced resections in malignant glioma surgery using a well-characterized tool for intraoperative tumor visualization, 5-aminolevulinic acid (5-ALA). OBJECTIVE: To evaluate the cost-effectiveness of 5-ALA fluorescence-guided neurosurgery compared with white-light surgery in adult patients with newly diagnosed high-grade glioma, adopting the perspective of the Portuguese National Health Service. METHODS: We used a Markov model (cohort simulation). Transition probabilities were estimated with the use of data from 1 randomized clinical trial and 1 noninterventional prospective study. Utility values and resource use were obtained from published literature and expert opinion. Unit costs were taken from official Portuguese reimbursement lists (2012 values). The health outcomes considered were quality-adjusted life-years, lifeyears, and progression-free life-years. Extensive 1-way and probabilistic sensitivity analyses were performed. RESULTS: The incremental cost-effectiveness ratios are below €10 000 in all evaluated outcomes, being around €9100 per quality-adjusted life-year gained, €6700 per life-year gained, and €8800 per progression-free life-year gained. The probability of 5-ALA fluorescence-guided surgery cost-effectiveness at a threshold of €20000 is 96.0% for quality-adjusted life-year, 99.6% for life-year, and 98.8% for progression-free life-year. CONCLUSION: 5-ALA fluorescence-guided surgery appears to be cost-effective in newly diagnosed high-grade gliomas compared with white-light surgery. This example demonstrates cost-effectiveness analyses for malignant glioma surgery to be feasible on the basis of existing data.

Cost-Effectiveness of Non-Vitamin K Antagonist Oral Anticoagulants for Atrial Fibrillation in Portugal

INTRODUCTION AND OBJECTIVES:Recently, three novel non-vitamin K antagonist oral anticoagulants received approval for reimbursement in Portugal for patients with non-valvular atrial fibrillation (AF). It is therefore important to evaluate the relative cost-effectiveness of these new oral anticoagulants in Portuguese AF patients. METHODS: A Markov model was used to analyze disease progression over a lifetime horizon. Relative efficacy data for stroke (ischemic and hemorrhagic), bleeding (intracranial, other major bleeding and clinically relevant non-major bleeding), myocardial infarction and treatment discontinuation were obtained by pairwise indirect comparisons between apixaban, dabigatran and rivaroxaban using warfarin as a common comparator. Data on resource use were obtained from the database of diagnosis-related groups and an expert panel. Model outputs included life years gained, quality-adjusted life years (QALYs), direct healthcare costs and incremental cost-effectiveness ratios (ICERs). RESULTS:Apixaban provided the most life years gained and QALYs. The ICERs of apixaban compared to warfarin and dabigatran were €5529/QALY and €9163/QALY, respectively. Apixaban was dominant over rivaroxaban (greater health gains and lower costs). The results were robust over a wide range of inputs in sensitivity analyses. Apixaban had a 70% probability of being cost-effective (at a threshold of €20 000/QALY) compared to all the other therapeutic options. CONCLUSIONS:Apixaban is a cost-effective alternative to warfarin and dabigatran and is dominant over rivaroxaban in AF patients from the perspective of the Portuguese national healthcare system. These conclusions are based on indirect comparisons, but despite this limitation, the information is useful for healthcare decision-makers.

Three essays on the term structure of interest rates

A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

2D position system for a mobile robot in unstructured environments

Nowadays, several sensors and mechanisms are available to estimate a mobile robot trajectory and location with respect to its surroundings. Usually absolute positioning mechanisms are the most accurate, but they also are the most expensive ones, and require pre installed equipment in the environment. Therefore, a system capable of measuring its motion and location within the environment (relative positioning) has been a research goal since the beginning of autonomous vehicles. With the increasing of the computational performance, computer vision has become faster and, therefore, became possible to incorporate it in a mobile robot. In visual odometry feature based approaches, the model estimation requires absence of feature association outliers for an accurate motion. Outliers rejection is a delicate process considering there is always a trade-off between speed and reliability of the system. This dissertation proposes an indoor 2D position system using Visual Odometry. The mobile robot has a camera pointed to the ceiling, for image analysis. As requirements, the ceiling and the oor (where the robot moves) must be planes. In the literature, RANSAC is a widely used method for outlier rejection. However, it might be slow in critical circumstances. Therefore, it is proposed a new algorithm that accelerates RANSAC, maintaining its reliability. The algorithm, called FMBF, consists on comparing image texture patterns between pictures, preserving the most similar ones. There are several types of comparisons, with different computational cost and reliability. FMBF manages those comparisons in order to optimize the trade-off between speed and reliability.